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📄 kolmogorov_smirnov_cdf.m

📁 similer program for matlab
💻 M
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## Copyright (C) 1995, 1996, 1997, 1998, 2000, 2002, 2004, 2005, 2006,##               2007 Kurt Hornik#### This file is part of Octave.#### Octave is free software; you can redistribute it and/or modify it## under the terms of the GNU General Public License as published by## the Free Software Foundation; either version 3 of the License, or (at## your option) any later version.#### Octave is distributed in the hope that it will be useful, but## WITHOUT ANY WARRANTY; without even the implied warranty of## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU## General Public License for more details.#### You should have received a copy of the GNU General Public License## along with Octave; see the file COPYING.  If not, see## <http://www.gnu.org/licenses/>.## -*- texinfo -*-## @deftypefn {Function File} {} kolmogorov_smirnov_cdf (@var{x}, @var{tol})## Return the CDF at @var{x} of the Kolmogorov-Smirnov distribution,## @iftex## @tex## $$ Q(x) = \sum_{k=-\infty}^\infty (-1)^k \exp(-2 k^2 x^2) $$## @end tex## @end iftex## @ifinfo## @example##          Inf## Q(x) =   SUM    (-1)^k exp(-2 k^2 x^2)##        k = -Inf## @end example## @end ifinfo#### @noindent## for @var{x} > 0.#### The optional parameter @var{tol} specifies the precision up to which## the series should be evaluated;  the default is @var{tol} = @code{eps}.## @end deftypefn## Author: KH <Kurt.Hornik@wu-wien.ac.at>## Description: CDF of the Kolmogorov-Smirnov distributionfunction cdf = kolmogorov_smirnov_cdf (x, tol)  if (nargin < 1 || nargin > 2)    print_usage ();  endif  if (nargin == 1)    tol = eps;  else    if (! isscalar (tol) || ! (tol > 0))      error ("kolmogorov_smirnov_cdf: tol has to be a positive scalar");    endif  endif  n = numel (x);  if (n == 0)    error ("kolmogorov_smirnov_cdf: x must not be empty");  endif  cdf = zeros (size (x));  ind = find (x > 0);  if (length (ind) > 0)    if (size(ind,2) < size(ind,1))      y = x(ind.');    else      y   = x(ind);    endif    K   = ceil (sqrt (- log (tol) / 2) / min (y));    k   = (1:K)';    A   = exp (- 2 * k.^2 * y.^2);    odd = find (rem (k, 2) == 1);    A(odd,:) = -A(odd,:);    cdf(ind) = 1 + 2 * sum (A);  endifendfunction

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